Multiple Query Probabilistic Roadmap Planning Using Single Query Planning Primitives

Publication Type:

Conference Paper

Authors:

Bekris, K.E.; Chen, B.Y.; Ladd, A.M.; Plaku, E.; Kavraki, L.E.

Source:

2003 IEEE/RJS International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, p.656-661 (2003)

URL:

http://www.kavrakilab.org/sites/default/files/PaperIROS_SRT-h.pdf

Keywords:

path planning; project_SRT

Abstract:

We propose the combination of techniques that solve
multiple queries for motion planning problems with single query
planners. Our implementation uses a probabilistic roadmap method PRM
with bidirectional rapidly exploring random trees BIRRT as the local
planner. With small modifications to the standard algorithms, we
obtain a multiple query planner which is significantly faster and
more reliable than its component parts. Our method provides a smooth
spectrum between the PRM and BIRRT techniques and obtains the
advantages of both. We observed that the performance differences are
most notable in planning instances with several rigid non-convex
robots in a scene with narrow passages. This planner is in the
spirit of non-uniform sampling and refinement techniques used in
earlier work on PRM.